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A decision framework for management of conflicting production and biodiversity goals for a commercially valuable invasive species

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AGRICULTURAL SYSTEMS 2014年 125卷 1-11页

作者： Grechi, Isabelle Chades, Iadine Buckley, Yvonne M. Friedel, Margaret H. Grice, Anthony C. Possingham, Hugh P. van Klinken, Rieks D. Martin, Tara G. CSIRO Dutton Pk Qld Australia INRA Plantes & Syst Culture Hort UR1115 F-84914 Avignon 9 France CIRAD UPR HortSys F-34398 Montpellier 5 France Univ Queensland Sch Biol Sci ARC Ctr Excellence Environm Decis Brisbane Qld 4072 Australia CSIRO Alice Springs NT Australia CSIRO Townsville Qld Australia

The management of introduced species that are both invasive and commercially valuable is contentious. While such species provide substantial economic benefits to some, they pose considerable costs to others due to negative impacts on ecosystems. We propose a decision framework to help balance conflicting objectives and support the management of commercially valuable invasive species. We illustrate our framework using the buffel grass (Pennisetum ciliare syn. Cenchrus ciliaris L.) invasion in Australia. In rangelands worldwide, buffet grass is amongst a suite of commercially valuable invasive species, highly valued by some graziers as a pasture species but widely unpopular among those concerned with the threat it poses for native biodiversity. The framework comprises four components. First we develop a state and transition model to represent the invasion dynamics of buffel grass and the effect of management actions. Second we construct utility functions to represent the relative values of buffel grass cover in terms of production and biodiversity utilities (indicative of grazier's and conservationist's relative 'happiness' regarding buffel grass cover). We draw on expert and empirical data for the construction of the model and utility functions. Third, we present management strategies that minimize losses in production and biodiversity utilities in the absence of budget constraints. We use stochastic dynamic programming and multi-criteria decision analysis which explicitly account for trade-offs between production and biodiversity conservation concerns. Finally, we conduct a sensitivity analysis to assess the impact of assumptions of the model and utility functions. Management complexity arises from biodiversity-production trade-off situations in which the desirable state of buffel grass cover and effective actions to achieve this state depend on the utility functions. Management solutions were particularly sensitive to the shape of the utility functions for biodiver

关键词： Buffel grass Decision theory Optimization State and transition model stochastic dynamic programming Utility functions

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The Behavioral Ecology of Fishing Vessels: Achieving Conservation Objectives Through Understanding the Behavior of Fishing Vessels

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ENVIRONMENTAL & RESOURCE ECONOMICS 2015年第1期61卷 71-85页

作者： Mangel, Marc Dowling, Natalie Arriaza, Juan Lopez Univ Calif Santa Cruz Ctr Stock Assessment Res Santa Cruz CA 95064 USA Univ Calif Santa Cruz Dept Appl Math & Stat Santa Cruz CA 95064 USA Univ Bergen Dept Biol N-9020 Bergen Norway CSIRO Marine & Atmospher Res Castray Esplanade Hobart Tas 7001 Australia

Colin Clark made seminal contributions in both resource economics and behavioral ecology. In the former, he showed how to link biological and economic factors in a consistent mathematical framework, virtually creating the field of mathematical bioeconomics single-handedly. In the latter, he was a major contributor of the introduction of state variable methods for modeling the behavior and life history of organisms. In this paper, we apply the methods of behavioral ecology to a problem in fisheries management and show that understanding fisher responses to quota decrements according to fishing area (so that the decrement in the quota of effort from fishing in a particular area is larger than the actual effort used there) may be as or more effective for seabird conservation than closing areas. To begin, we explain state variable methods in behavioral ecology, using insect parasitoids-Colin's choice of after dinner talk at the meeting in his honor-making connections between behavioral ecology and resource economics. We then turn to the pelagic longline fishery off eastern Australia and show how the same kinds of methods used in behavioral ecology can provide new insights about this fishery. We provide a model of sufficient detail to compare the current management practice (closures), no management, and spatial management with effort decrements that vary over space and show that the latter management strategy is both environmentally and economically more effective than closures or no management.

关键词： Bioeconomics Behavioral ecology State dependence stochastic dynamic programming Fisheries

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Unreliable newsboy problem with a forecast update

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OPERATIONS RESEARCH LETTERS 2011年第4期39卷 278-282页

作者： Tiwari, Divya Patil, Rahul Shah, Janat IIM Bangalore Bangalore 560076 Karnataka India Indian Inst Technol SJMSOM Bombay 400076 Maharashtra India

In this paper, we derive an optimal ordering policy for an unreliable newsboy who can place two sequential orders before the start of a single selling season by using a demand forecast update. Supply yield is modeled using a uniform distribution considering both the minimum order guarantee and the maximum yield. Our results indicate that a firm should focus on increasing the minimum order guarantee from a first stage supplier to reduce its total supply chain cost. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Newsboy problem Forecast update Random yield Inventory management stochastic dynamic programming

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Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2020年 202卷 106994-106994页

作者： Yan, Tao Lei, Yaguo Wang, Biao Han, Tianyu Si, Xiaosheng Li, Naipeng Xi An Jiao Tong Univ Educ Minist Modern Design & Rotor Bearing Syst Key Lab Xian 710049 Shaanxi Peoples R China

Joint maintenance and spare parts inventory optimization has attracted increasing attention in recent years because of its capability in addressing the maintenance planning and the spare parts provisioning of industrial systems simultaneously. However, imperfect maintenance (IM) actions are either neglected or over-simplified as constant improvements in existing studies, which reduces their practicality in industrial applications. To tackle this limitation, this paper investigates the joint maintenance and spare parts inventory optimization for multi-unit systems with the consideration of IM actions as random improvement factors. First, a two-step approximate derivation method is proposed, which overcomes the derivation difficulties of replacement numbers due to the introduction of random improvement factors and enables the construction of the inventory level transition relationship. Then based on the inventory level transition relationship, an expected total cost model is formulated via the finite horizon stochastic dynamic programming (FHSDP). The decision variables are optimized by the joint use of enumeration and the FHSDP. Finally, a numerical simulation of a wind farm is carried out for illustration. Sensitivity analyses are further conducted to study the influences of critical parameters.

关键词： Imperfect maintenance Joint optimization stochastic dynamic programming Multi-unit systems

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Multistage System Planning for Hydrogen Production and Distribution

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NETWORKS & SPATIAL ECONOMICS 2010年第4期10卷 455-472页

作者： Huang, Yongxi Fan, Yueyue Johnson, Nils Univ Calif Davis Dept Civil & Environm Engn Inst Transportat Studies Davis CA 95616 USA

Hydrogen is an energy carrier that has the potential to improve the sustainability of transportation fuels and reduce oil dependence. This paper presents a stochastic dynamic programming model for sequentially building a hydrogen production and distribution system. The decision variables are the sequence and locations of the central production sites and the corresponding distribution systems from supply to demand sites. A case study based on the geographic setting of Northern California is included, in which the hydrogen is produced via coal gasification and transported from plant to city gates (demand sites) by cryogenic liquid hydrogen trucks. Future demands for hydrogen are modeled as uncertain parameters, with an assumption that hydrogen fuel cell vehicle (HFCV) market penetration rate increases from 1% to 25% over a 20-year period. This model provides multistage decision support for long term transportation energy planning at national and regional levels.

关键词： Multistage processes Energy infrastructure system planning stochastic dynamic programming Hydrogen transition

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GPU based generation of state transition models using simulations for unmanned surface vehicle trajectory planning

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ROBOTICS AND AUTONOMOUS SYSTEMS 2012年第12期60卷 1457-1471页

作者： Thakur, Atul Svec, Petr Gupta, Satyandra K. Univ Maryland Dept Mech Engn College Pk MD 20742 USA Univ Maryland Syst Res Inst College Pk MD 20742 USA

This paper describes CPU based algorithms to compute state transition models for unmanned surface vehicles (USVs) using 6 degree of freedom (DOF) dynamics simulations of vehicle-wave interaction. A state transition model is a key component of the Markov Decision Process (MDP), which is a natural framework to formulate the problem of trajectory planning under motion uncertainty. The USV trajectory planning problem is characterized by the presence of large and somewhat stochastic forces due to ocean waves, which can cause significant deviations in their motion. Feedback controllers are often employed to reject disturbances and get back on the desired trajectory. However, the motion uncertainty can be significant and must be considered in the trajectory planning to avoid collisions with the surrounding obstacles. In case of USV missions, state transition probabilities need to be generated on-board, to compute trajectory plans that can handle dynamically changing USV parameters and environment (e.g., changing boat inertia tensor due to fuel consumption, variations in damping due to changes in water density, variations in sea-state, etc.). The 6 DOF dynamics simulations reported in this paper are based on potential flow theory. We also present a model simplification algorithm based on temporal coherence and its CPU implementation to accelerate simulation computation performance. Using the techniques discussed in this paper we were able to compute state transition probabilities in less than 10 min. Computed transition probabilities are subsequently used in a stochastic dynamic programming based approach to solve the MDP to obtain trajectory plan. Using this approach, we are able to generate dynamically feasible trajectories for USVs that exhibit safe behaviors in high sea-states in the vicinity of static obstacles. (C) 2012 Elsevier B.V. All rights reserved.

关键词： USV Vehicle simulation Fluid-rigid interaction GP-GPU Trajectory planning MDP State transition map stochastic dynamic programming Motion uncertainty

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Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

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WATER RESOURCES MANAGEMENT 2014年第10期28卷 3127-3142页

作者： Rehana, S. Mujumdar, P. P. Malla Reddy Inst Technol & Sci Dept Civil Engn Hyderabad 500014 Andhra Pradesh India Indian Inst Sci Dept Civil Engn Bangalore 560012 Karnataka India Indian Inst Sci Divecha Ctr Climate Change Bangalore 560012 Karnataka India

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.

关键词： Climate change Statistical downscaling Reservoir rule curves stochastic dynamic programming Fuzzy optimization

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A comparison of two methods for multiobjective optimization for reservoir operation

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WATER RESOURCES BULLETIN 1996年第2期32卷 333-340页

作者： Liang, QF Johnson, LE Yu, YS UNIV COLORADO DEPT CIVIL ENGNDENVERCO 80217 UNIV KANSAS DEPT CIVIL ENGNLAWRENCEKS 66045

Two major objectives in operating the multireservoir system of the Upper Colorado River basin are maximization of hydroelectric power production and maximization of the reliability of annual water supply. These two objectives conflict. Optimal operation of the reservoir system to achieve both is unattainable. This paper seeks the best compromise solution for an aggregated reservoir as a surrogate of the multireservoir system by using two methods: the constraint method and the method of combined stochastic and deterministic modeling. Both methods are used to derive the stationary optimal operating policy for the aggregated reservoir by using stochastic dynamic programming but with different objective functions and minimum monthly release constraints. The resulting operating policies are then used in simulated operation of the reservoir with historical inflow records to evaluate their relative effectiveness. The results show that the policy obtained from the combination method would yield more hydropower production and higher reliability of annual water supply than that from the constraint-method policy.

关键词： multiobjective optimization water supply hydropower stochastic dynamic programming reliability

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Structured threshold policies for dynamic sensor scheduling - A partially observed Markov decision process approach

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2007年第10期55卷 4938-4957页

作者： Krishnamurthy, Vikram Djonin, Dejan V. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada Univ British Columbia Dyaptive Syst Inc Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

We consider the optimal sensor scheduling problem formulated as a partially observed Markov decision process (POMDP). Due to operational constraints, at each time instant, the scheduler can dynamically select one out of a finite number of sensors and record a noisy measurement of an underlying Markov chain. The aim is to compute the optimal measurement scheduling policy, so as to minimize a cost function comprising of estimation errors and measurement costs. The formulation results in a nonstandard POMDP that is nonlinear in the information state. We give sufficient conditions on the cost function, dynamics of the Markov chain and observation probabilities so that the optimal scheduling policy has a threshold structure with respect to a monotone likelihood ratio (MLR) ordering. As a result, the computational complexity of implementing the optimal scheduling policy is inexpensive. We then present stochastic approximation algorithms for estimating the best linear MLR order threshold policy.

关键词： bayesian filtering monotone likelihood ratio (MLR) ordering partially observed Markov decision processes (POMDPs) sensor scheduling stochastic approximation algorithms stochastic dynamic programming threshold policies

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A qualitative approach to Markovian equilibrium on optimal growth under uncertainty

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JOURNAL OF dynamicAL AND CONTROL SYSTEMS 2006年第4期12卷 451-464页

作者： Carpio, L. G. T. Univ Fed Rio de Janeiro COPPE Energy Planning Program BR-21945 Rio De Janeiro Brazil

This paper develops a discretized version of a stochastic model of the economic growth and studies its convergence and stability properties. A nonlinear model of the economic growth, which involves the production, technology stock, and their rates as the main variables, is considered. We analyze the case where the production function does not satisfy the Inada conditions and we show that, in this case, a sufficient condition for the existence of a unique steady state is that the marginal utility function should possess a horizontal and vertical asymptotic elasticity.

关键词： natural resources optimal growth stochastic dynamic programming asymptotic stability

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